components of plant species diversity in the new zealand forest jake overton landcare research...
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Components of plant species diversity in the New Zealand forest
Jake Overton
Landcare Research
Hamilton
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Acknowledgements
NVS data contributors and curators
Simon Ferrier and Glenn Manion for development of GDM and collaboration on modelling
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General Question
Investigate components of richness
• Alpha diversity
• Beta diversity
• Gamma diversity
How do these compare between groups?
Approach: Use a new modelling technique, Generalised Dissimilarity Modelling (GDM) to estimate components of diversity
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Components of diversity (sensu Cody 1986)
Alpha diversity = local richness
Beta diversity = turnover in species due to habitat or environment
Gamma diversity = turnover in species due to geographic distance or barriers
All three components contribute to regional richness
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Presence-absence of all vascular plant species in each plot
Plots approx 20x20 m (sometimes unbounded)
Almost 20000 plots
1220 species
NVS recce (= recon) plots
Biotic Data
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Variable abbrev. Description
Geographic position Geographic position of plot
MAT Mean Annual Temperature
Tseas A measure of cold stress, relative to mean annual temperature
MAS Mean Annual Solar Radiation
Deficit Vapor Pressure deficit
VPD Vapor Pressure deficit
Calcium Soil Calcium
Age Soil age
N Total Soil Nitrogen
AcidP Available P
Drain Soil Drainage
Psize Soil Particle Size
Indur Soil Induration
Slope Topographic slope
Discoast Distance to coastline
Notho Nothofagus abundance from Leathwick
En
viro
nm
enta
l va
riab
les
(sp
atia
l)
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alpha diversity (local richness)
beta diversity
gamma diversity
‘dissimilarity’‘turnover’‘complementarity’
richness = f (rainfall, temperature, veg type …)
dissimilarity = f ( (rainfall, temperature, veg type …), geographical separation)
Modelling of richness:
can be supplemented by modelling of compositional dissimilarity between locations:
What is Generalised Dissimilarity Modelling?
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Compositional dissimilarity between pairs of survey sites
Environmental& geographicalseparation
Generalised dissimilarity modelling (GDM)
Biotic Information
Environmental and Geog Space
Ecological Space
Same units scaled by importance
Diff
erin
g un
its a
ndim
port
ance
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All
sp
ecie
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od
el
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Results 1
All
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lid
atio
n
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1ln
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All species
Total species pool 1020 species
Alpha diversity component = Proportion accounted for by local richness = Mean plot richness/ Total species pool
Unexplained component = 1 – proportion deviance explained
Gamma Diversity component = Proportion deviance explained by geography
Beta Diversity component = Deviance explained by environment
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All plant speciesSnails
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Group # spp local rich
Ferns 147 6.8
Lianes-epiphytes-parasites
49 1.9
Trees 107 8.9
Shrubs 255 4.3
Dicot herbs 360 2.4
Monocot herbs 282 1.3
All Species 1020 25.9
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Results 1
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All
Ferns
Shrubs
Trees
Monocot herbs
Dicot Herbs
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All species
Dicot HerbsFerns
Monocot herbs
Shrubs
Trees
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Biological survey data
Environmentalpredictors
Visualisation of spatial pattern in community composition
Predicted distributions of species
Constrained environmental classification
Survey gap analysis
Conservation assessment
Climate-change impact assessment
Generalised dissimilarity modelling
Ferrier, S. et al (in press) Using generalised dissimilarity modelling to analyse and predict patterns of beta-diversity in regional biodiversity assessment. Diversity & Distributions
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Ferrier, S. et al (2004) Mapping more of terrestrial biodiversity for global conservation assessment. BioScience 54: 1101-1109
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Conclusions
GDM is an exciting new tool for biodiversity analyses
Its main application is for biodiversity modelling and planning, but it has promise for untangling components of diversity
Plant species show relatively strong environmental influence and some geographic influence on turnover
Groups differ in the explained turnover, and in relative importance of different variables.
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test
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Dense sampling relative to grain of compositional turnover - relatively few species, each with many records
Sparse sampling relative to grain of compositional turnover - huge number of species, each with very few (or no) records
Environmental space (beta diversity)
Geogra
phic
al sp
ace
(gam
ma d
ivers
ity)
Geogra
phic
al sp
ace
(gam
ma d
ivers
ity)
Environmental space (beta diversity)
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An example from the arid rangelands of central Australia
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All species
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All species
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Environmental predictors•Radiometrics – Total Count•Landsat TM – Band 2•Radiation of Warmest Quarter•Topographic Wetness Index •Precipitation of Driest Period•Isothermality•Minimum Temperature of Coldest Period•Elevation Diversity for 300m radius•Landsat TM – PD54 vegetation index•Mean Temperature of Wettest Quarter•Radiometrics – Uranium
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f (W
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)
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Biological responseBray-Curtis compositional dissimilarity between all pairs of 248 field survey sites (based on perennial woody plant species)
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Models species turnover (dissimilarity) between locations as a function of geography and environment
Uses matrix regression, using GLMs.
Developed by Simon Ferrier, (Department of Environment and Conservation, Armidale New South Wales, Australia)
Programmed by Glenn Manion, DEC, Armidale.
What is Generalised Dissimilarity Modelling?
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All species
Dicot HerbsFerns
Monocot herbs
Shrubs
Trees
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FernsFerns
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test
L-E-P
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Monocot herbs
Monocot herbs
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Shrubs
Shrubs
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Trees
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test
Dicot Herbs
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Ferns
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test
L-E-P
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Monocot herbs
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Shrubs
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Trees
Trees